Key takeaways from our Strategy & AI webinar

Following the positive reception of our previous post on ‘Generative AI as part of strategy work’, we decided to organize a webinar featuring Tero Ojanperä, Co-Founder of Silo AI, Professor of Practice, and author of the book ‘Tekoälyn vallankumous‘ (AI Revolution), alongside Jussi Siitonen, CFO of Fiskars and a keen AI enthusiast. The aim was to broaden the discussion about AI’s practical applications and implications. Here are some selected highlights from our engaging session: 

AI Landscape (by Tero Ojanperä) 

  • Future predictions indicate that 90% of text, images, and other content will be generated by GenAI. Given that major GenAI players (e.g. Microsoft, OpenAI, Google, Meta, and Adobe), come from the US, it is critical for other regions, including the EU, to strengthen their AI capabilities. This would ensure a diverse representation of perspectives in shaping AI’s future and the content it creates 
  • There are various ways to improve language models’ answer quality, such as prompt engineering and finetuning. However, specialized models, built with context-specific data from scratch, stand out as particularly exciting. These models, closely tied to specific contexts, offer superior answers compared to more generic foundation models 
  • Maturity framework describing organization’s GenAI usage consists of three phases: ‘Try & Learn,’ ‘Productivity,’ and ‘New and Better Products‘. The last phase involves creating novel AI-based products and services that are context-specific, relying on the previously mentioned specialized models. In the future these models, which are often trained with companies’ own internal data, can become a central source of competitive advantage 

GenAI and Strategy Work (by Jori Stjerna) 

  • Since the beginning of the year, August has incorporated ChatGPT-4 into various projects. The next step involves ramping up the Azure OpenAI service, opening new opportunities to handle proprietary data (e.g. summarizing key points from interviews, structuring large data sets) 
  • Publicly available GenAI solutions prove most effective for analyzing external data and providing qualitative answers. This includes tasks like building future scenarios, creating brand positioning tables, and synthesizing feedback on the pros and cons of a consumer product 
  • Practical tips for using ChatGPT-4 include 1) Requesting prompting instructions directly from the solution, 2) Regularly checking if OpenAI has released new ChatGPT capabilities, and 3) Maintaining curiosity to experiment the tool to find new use cases 

Commentary from a Business Leader’s Perspective (by Jussi Siitonen) 

  • There are two key ways to benefit from GenAI: leveraging specialized models for organization’s internal data and adopting general productivity-increasing GenAI solutions, such as Copilot or Bing Chat Enterprise 
  • Primary concern is preventing GenAI tools from remaining restricted to a selected expert group within an organization. Encouraging curiosity and playfulness with AI can help mitigate this challenge 
  • At Fiskars, there’s considerable excitement surrounding GenAI. Practical cases include value-added GenAI applications offered alongside Fiskars products, such as an AI gardening coach, and in internal context the handling and summarization of extensive reports and documents 

I hope the selected highlights were useful and if you’d like to discuss more about GenAI and how to use it as an augmented team member in strategic assignment, feel free to reach out to Tomi Ere. Stay tuned for our next GenAI post, where we’ll look into August’s experience ramping up the Azure OpenAI service and share key lessons we have learned! 


Tomi Ere
+358 40 823 3848